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随机漂移误差是激光陀螺的主要误差源之一。Kalman滤波算法能够有效抑制激光陀螺的随机误差,但是当计算模型不准确时,采用常规Kalman滤波易导致结果发散。渐消Kalman滤波能够抑制历史信息、重用现时量测信息,得到连续平稳的滤波结果。采用渐消Kalman滤波对激光陀螺随机漂移进行最优估计,取得了较好的效果。结果表明,渐消Kalman滤波的残差标准差更小,输出序列更加平稳,滤波的精度和稳定性更高。
Random drift error is one of the main sources of error in a laser gyro. Kalman filter algorithm can effectively suppress the random error of the laser gyro, but when the calculation model is not accurate, the use of conventional Kalman filter can easily lead to divergence of results. The fading Kalman filter can suppress the historical information and reuse the current measurement information to obtain a continuous and smooth filtering result. Fading Kalman filter is used to optimize the stochastic drift of the laser gyro, and the better effect is achieved. The results show that the residual standard deviation of the fading Kalman filter is smaller, the output sequence is smoother, and the filtering accuracy and stability are higher.